Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: Sibendu Som Project Name: navistar_tbc Division: ES Project title: CFD study of dimensional variations on charge preparation and heat-release management in a multi-injector diesel engine Associated funding: In process Other Systems: TBD Science: Improving the fuel efficiency of diesel-engine can bring significant socio-economic benefits since, a significant fraction of US freight is transported by diesel-engine powered trucks. For a given engine architecture, the fuel-injection, air and after-treatment system determines the emissions and efficiency. A multi-hole, single injector per cylinder represents the traditional fuel-injection system. In this engine, fuel-distribution and mixing are restricted by the spray penetration and the strength of the in-cylinder charge motion. These limitations can be overcome by application of innovative concept of multiple-injector per cylinder design. This system provides enhanced flexibility for the fuel-air mixing process and the heat-release rate management for better performance and emissions. However, manufacturing process variations and tolerances in the injector and combustion system can impact the emission and performance. Therefore, this project proposes to computa tionally evaluate the effects of key manufacturing tolerances on the charge preparation process and thus on the engine performance Project description: A multi-hole, single injector represents the traditional fuel-injection system found in today’s production diesel engine. The injector is completely characterized by parameters such as the flow-rate, cone-angle, number of injector holes and the injector placement location. A common-rail injector can also have up to 5 injection events per cycle. In addition to the fuel-injection system variables, the inputs to the combustion system include parameters such as the swirl motion, intake and exhaust valve characteristics and the combustion system profile. Given such a large number of inputs, the combustion system has been traditionally optimized using computation fluid analysis (CFD). In the present study, the level of complexity is significantly higher as multiple number of injectors are implemented per cylinder. The central injectors are complemented with peripheral injectors. The peripheral injectors given their intrinsic location have different flow-char acteristics than the main injector and need to treated as a separate variable for the optimization process. The casting of the original cylinder head architecture will be extensively modified along with the machined features to accommodate the new injectors while providing the necessary cooling and durability to the engine. Given the spatially distributed nature of the heat-release process the new combustion is more susceptible to the manufacturing variations of various components, particularly cylinder head and the fuel injector. Therefore, accounting for all the design space for optimization needs to be carefully analyzed by high-fidelity engine simulations. Navistar would like to work with the Argonne National Laboratory (ANL) CFD team led by Dr.Sibendu Som for the analysis. Preliminary estimates indicate that several millions of core-hours of supercomputing will be needed to understand, optimize and characterize such a complicated combustion system. ANL with a proven tr ack record of implementing software innovations for supercomputing advances in the area of internal-combustion engine design and with a close proximity to the Navistar facility lends itself to be an ideal project partner for this endeavor. Industry partnership: TBD Project URL: http://www.transportation.anl.gov/engines/multi_dim_model_home.html Current FY Hours Used: undetermined amount New FY Requested allocation: 600000 Q1: 150000 Q2: 150000 Q3: 150000 Q4: 150000 Justification: Our recent publication (J. Kodavasal, K. Harms, P. Srivastava, S. Som, S. Quan, K.J. Richards, M. Garcia, “Development of stiffness-based chemistry load balancing scheme, and optimization of I/O and communication, to enable massively parallel high-fidelity internal combustion engine simulations,” Journal of Energy Resource Technology; JERT-16-1022, 2016) together with MCS and Convergent Science discusses the improvements to the Converge tool that has resulted in significant improvement in scaling. Currently, we are able to scale the code up to 4096 processors on Mira with about 70% scaling efficiency for a fixed mesh size. This was achieved due to the implementation of: (1) MPI I/O, (2) Improved Communication, (3) METIS load balancing scheme, (4) Development of a new chemistry load balancing scheme. The above changes are not only expected to benefit calculations on Mira but also help on computing clusters like Blues. Storage requirements: 5 TB Thank You, The LCRC Accounts System